1. Field of the Invention
The present invention relates to a method of adjusting a gain for motor control for a robot or the like, and more particularly to a method of automatically adjusting the feedback gain of a motor control loop.
2. Background of the Related Art
It is highly difficult to effect a feed-forward control process on a system, such as a robot, in which the inertia of a load varies to a large extent depending on whether the arm of the system is extended or contracted, and which has servomotors and mechanical movable parts with large speed-reduction ratios of mechanisms. This is because a feed-forward gain, which is not in a feedback loop, is ineffective unless parameters are in exact conformity with each other.
Heretofore, it has been impossible to calculate a feed-forward gain if the value of inertia is unknown. In the event that the inertia is subjected to a variation, it is very difficult to calculate an average inertia value, and highly cumbersome to do so when such a calculation is carried out.
One solution is disclosed in a patent application entitled "Method of learning a feed-forward gain for motor control", filed on Feb. 21, 1990 by the applicant. In the disclosed method, a feed-forward gain is determined according to a learning process.
A feedback gain of a feedback loop, i.e., a proportional gain or the like, is determined in view of a step response, etc., of the system.
When a feedback gain is determined in view of a step response, etc., however, it takes considerable time to measure the step response, etc. Since determination of a feedback gain requires a lot of skill on the part of the operator, difficulty has been experienced in objectively determining a proper value of feedback gain.